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Related papers: Controllable Long-term Motion Generation with Exte…

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Human motion synthesis is an important task in computer graphics and computer vision. While focusing on various conditioning signals such as text, action class, or audio to guide the generation process, most existing methods utilize…

Computer Vision and Pattern Recognition · Computer Science 2024-05-14 Kebing Xue , Hyewon Seo

Whole-body multi-modal human motion generation poses two primary challenges: creating an effective motion generation mechanism and integrating various modalities, such as text, speech, and music, into a cohesive framework. Unlike previous…

Computer Vision and Pattern Recognition · Computer Science 2025-10-17 Zhe Li , Weihao Yuan , Weichao Shen , Siyu Zhu , Zilong Dong , Chang Xu

Advances in video generation have significantly improved the realism and quality of created scenes. This has fueled interest in developing intuitive tools that let users leverage video generation as world simulators. Text-to-video (T2V)…

Computer Vision and Pattern Recognition · Computer Science 2026-04-03 Zuhao Liu , Aleksandar Yanev , Ahmad Mahmood , Ivan Nikolov , Saman Motamed , Wei-Shi Zheng , Xi Wang , Lei Sun , Luc Van Gool , Danda Pani Paudel

This paper addresses the challenge of text-conditioned streaming motion generation, which requires us to predict the next-step human pose based on variable-length historical motions and incoming texts. Existing methods struggle to achieve…

Computer Vision and Pattern Recognition · Computer Science 2025-08-08 Lixing Xiao , Shunlin Lu , Huaijin Pi , Ke Fan , Liang Pan , Yueer Zhou , Ziyong Feng , Xiaowei Zhou , Sida Peng , Jingbo Wang

Our goal is to populate digital environments, in which digital humans have diverse body shapes, move perpetually, and have plausible body-scene contact. The core challenge is to generate realistic, controllable, and infinitely long motions…

Computer Vision and Pattern Recognition · Computer Science 2022-04-20 Yan Zhang , Siyu Tang

Camera-controlled video-to-video (V2V) generation enables dynamic viewpoint synthesis from monocular footage, holding immense potential for interactive filmmaking and live broadcasting. However, existing implicit synthesis methods…

Computer Vision and Pattern Recognition · Computer Science 2026-05-08 Youcan Xu , Jiaxin Shi , Zhen Wang , Wensong Song , Feifei Shao , Chen Liang , Jun Xiao , Long Chen

Recent interactive video world model methods generate scene evolution conditioned on user instructions. Although they achieve impressive results, two key limitations remain. First, they exhibit motion drift in complex environments with…

Computer Vision and Pattern Recognition · Computer Science 2026-03-19 Guangyuan Li , Bo Li , Jinwei Chen , Xiaobin Hu , Lei Zhao , Peng-Tao Jiang

Controllable human motion synthesis is essential for applications in AR/VR, gaming and embodied AI. Existing methods often focus solely on either language or full trajectory control, lacking precision in synthesizing motions aligned with…

Computer Vision and Pattern Recognition · Computer Science 2024-07-25 Weilin Wan , Zhiyang Dou , Taku Komura , Wenping Wang , Dinesh Jayaraman , Lingjie Liu

Efficient long-short temporal modeling is key for enhancing the performance of action recognition task. In this paper, we propose a new two-stream action recognition network, termed as MENet, consisting of a Motion Enhancement (ME) module…

Computer Vision and Pattern Recognition · Computer Science 2021-07-01 Liyu Wu , Yuexian Zou , Can Zhang

In this paper, we explore the overlooked challenge of stability and temporal consistency in interactive video generation, which synthesizes dynamic and controllable video worlds through interactive behaviors such as camera movements and…

Computer Vision and Pattern Recognition · Computer Science 2026-01-22 Ying Yang , Zhengyao Lv , Tianlin Pan , Haofan Wang , Binxin Yang , Hubery Yin , Chen Li , Ziwei Liu , Chenyang Si

Video generation models offer a promising imagination mechanism for robot manipulation by predicting long-horizon future observations, but effectively exploiting these imagined futures for action execution remains challenging. Existing…

Robotics · Computer Science 2026-05-13 Yajie Li , Bozhou Zhang , Chun Gu , Zipei Ma , Jiahui Zhang , Jiankang Deng , Xiatian Zhu , Li Zhang

Recent years have seen substantial progress in diffusion-based controllable video generation. However, achieving precise control in complex scenarios, including fine-grained object parts, sophisticated motion trajectories, and coherent…

Computer Vision and Pattern Recognition · Computer Science 2025-01-07 Haitao Zhou , Chuang Wang , Rui Nie , Jinlin Liu , Dongdong Yu , Qian Yu , Changhu Wang

Over recent years, diffusion models have facilitated significant advancements in video generation. Yet, the creation of face-related videos still confronts issues such as low facial fidelity, lack of frame consistency, limited editability…

Computer Vision and Pattern Recognition · Computer Science 2023-12-22 Linze Li , Sunqi Fan , Hengjun Pu , Zhaodong Bing , Yao Tang , Tianzhu Ye , Tong Yang , Liangyu Chen , Jiajun Liang

Text-guided motion editing enables high-level semantic control and iterative modifications beyond traditional keyframe animation. Existing methods rely on limited pre-collected training triplets, which severely hinders their versatility in…

Computer Vision and Pattern Recognition · Computer Science 2025-09-15 Nan Jiang , Hongjie Li , Ziye Yuan , Zimo He , Yixin Chen , Tengyu Liu , Yixin Zhu , Siyuan Huang

Recent advances in generative modeling and tokenization have driven significant progress in text-to-motion generation, leading to enhanced quality and realism in generated motions. However, effectively leveraging textual information for…

Computer Vision and Pattern Recognition · Computer Science 2025-02-05 Che-Jui Chang , Qingze Tony Liu , Honglu Zhou , Vladimir Pavlovic , Mubbasir Kapadia

Controllable generation is one of the key requirements for successful adoption of deep generative models in real-world applications, but it still remains as a great challenge. In particular, the compositional ability to generate novel…

Computer Vision and Pattern Recognition · Computer Science 2021-12-07 Weili Nie , Arash Vahdat , Anima Anandkumar

In computer animation, driving a simulated character with lifelike motion is challenging. Current generative models, though able to generalize to diverse motions, often pose challenges to the responsiveness of end-user control. To address…

Computer Vision and Pattern Recognition · Computer Science 2024-06-27 Yuxuan Mu , Shihao Zou , Kangning Yin , Zheng Tian , Li Cheng , Weinan Zhang , Jun Wang

Generating human videos with realistic and controllable motions is a challenging task. While existing methods can generate visually compelling videos, they lack separate control over four key video elements: foreground subject, background…

Computer Vision and Pattern Recognition · Computer Science 2025-08-13 Jingyun Liang , Jingkai Zhou , Shikai Li , Chenjie Cao , Lei Sun , Yichen Qian , Weihua Chen , Fan Wang

Recent progress in video diffusion models has markedly advanced character animation, which synthesizes motioned videos by animating a static identity image according to a driving video. Explicit methods represent motion using skeleton,…

Computer Vision and Pattern Recognition · Computer Science 2026-02-10 Zhufeng Xu , Xuan Gao , Feng-Lin Liu , Haoxian Zhang , Zhixue Fang , Yu-Kun Lai , Xiaoqiang Liu , Pengfei Wan , Lin Gao

An aerial manipulator, comprising a multirotor base and a robotic arm, is subject to significant dynamic coupling between these two components. Therefore, achieving precise and robust motion control is a challenging yet important objective.…

Robotics · Computer Science 2025-12-30 Mengyu Ji , Shiliang Guo , Zhengzhen Li , Jiahao Shen , Huazi Cao , Shiyu Zhao